#deeplearning.ai

[mr-entj]

Hello Mr. ENTJ. I'm an ENTJ sp/so 3 woman in her early twenties with a similar story to yours (Asian immigrant with a chip on her shoulder, used going to university as a way to break generational cycles). I graduated last month and have managed to break into strategy consulting with a firm that specialises in AI. Given your insider view into AI and your experience also starting out as a consultant, I would love to hear about any insights you might have or advice you may have for someone in my position. I would also be happy to take this discussion to somewhere like Discord if you'd prefer not to share in public/would like more context on my situation. Thank you!

Insights for your career or insights on AI in general?

On management consulting as a career, check the #management consulting tag.

On being a consultant working in AI:

Develop a solid understanding of the technical foundation behind LLMs. You don’t need a computer science degree, but you should know how they’re built and what they can do. Without this knowledge, you won’t be able to apply them effectively to solve any real-world problems. A great starting point is deeplearning.ai by Andrew Ng: Fundamentals, Prompt Engineering, Fine Tuning

Know all the terminology and definitions. What's fine tuning? What's prompt engineering? What's a hallucination? Why do they happen? Here's a good starter guide.

Understand the difference between various models, not just in capabilities but also training, pricing, and usage trends. Great sources include Artificial Analysis and Hugging Face.

Keep up to date on the newest and hottest AI startups. Some are hype trash milking the AI gravy train but others have actual use cases. This will reveal unique and interesting use cases in addition to emerging capabilities. Example: Forbes List.

On the industry of AI:

It's here to stay. You can't put the genie back in the bottle (for anyone reading this who's still a skeptic).

AI will eliminate certain jobs that are easily automated (ex: quality assurance engineers) but also create new ones or make existing ones more important and in-demand (ex: prompt engineers, machine learning engineers, etc.)

The most valuable career paths will be the ones that deal with human interaction, connection, and communication. Soft skills are more important than ever because technical tasks can be offloaded to AI. As Sam Altman once told me in a meeting: "English is the new coding language."

Open source models will win (Llama, Mistral, Deep Seek) because closed source models don't have a moat. Pick the cheapest model because they're all similarly capable.

The money is in the compute, not the models -- AI chips, AI infrastructure, etc. are a scarce resource and the new oil. This is why OpenAI ($150 billion valuation) is only 5% the value of NVIDIA (a $3 trillion dollar behemoth). Follow the compute because this is where the growth will happen.

America and China will lead in the rapid development and deployment of AI technology; the EU will lead in regulation. Keep your eye on these 3 regions depending on what you're looking to better understand.

[samarthdas]

Exploring DeepSeek and the Best AI Certifications to Boost Your Career

Understanding DeepSeek: A Rising AI Powerhouse

DeepSeek is an emerging player in the artificial intelligence (AI) landscape, specializing in large language models (LLMs) and cutting-edge AI research. As a significant competitor to OpenAI, Google DeepMind, and Anthropic, DeepSeek is pushing the boundaries of AI by developing powerful models tailored for natural language processing, generative AI, and real-world business applications.

With the AI revolution reshaping industries, professionals and students alike must stay ahead by acquiring recognized certifications that validate their skills and knowledge in AI, machine learning, and data science.

Why AI Certifications Matter

AI certifications offer several advantages, such as:

Enhanced Career Opportunities: Certifications validate your expertise and make you more attractive to employers.

Skill Development: Structured courses ensure you gain hands-on experience with AI tools and frameworks.

Higher Salary Potential: AI professionals with recognized certifications often command higher salaries than non-certified peers.

Networking Opportunities: Many AI certification programs connect you with industry experts and like-minded professionals.

Top AI Certifications to Consider

If you are looking to break into AI or upskill, consider the following AI certifications:

1. AICerts – AI Certification Authority

AICerts is a recognized certification body specializing in AI, machine learning, and data science.

It offers industry-recognized credentials that validate your AI proficiency.

Suitable for both beginners and advanced professionals.

2. Google Professional Machine Learning Engineer

Offered by Google Cloud, this certification demonstrates expertise in designing, building, and productionizing machine learning models.

Best for those who work with TensorFlow and Google Cloud AI tools.

3. IBM AI Engineering Professional Certificate

Covers deep learning, machine learning, and AI concepts.

Hands-on projects with TensorFlow, PyTorch, and SciKit-Learn.

4. Microsoft Certified: Azure AI Engineer Associate

Designed for professionals using Azure AI services to develop AI solutions.

Covers cognitive services, machine learning models, and NLP applications.

5. DeepLearning.AI TensorFlow Developer Certificate

Best for those looking to specialize in TensorFlow-based AI development.

Ideal for deep learning practitioners.

6. AWS Certified Machine Learning – Specialty

Focuses on AI and ML applications in AWS environments.

Includes model tuning, data engineering, and deep learning concepts.

7. MIT Professional Certificate in Machine Learning & Artificial Intelligence

A rigorous program by MIT covering AI fundamentals, neural networks, and deep learning.

Ideal for professionals aiming for academic and research-based AI careers.

Choosing the Right AI Certification

Selecting the right certification depends on your career goals, experience level, and preferred AI ecosystem (Google Cloud, AWS, or Azure). If you are a beginner, starting with AICerts, IBM, or DeepLearning.AI is recommended. For professionals looking for specialization, cloud-based AI certifications like Google, AWS, or Microsoft are ideal.

With AI shaping the future, staying certified and skilled will give you a competitive edge in the job market. Invest in your learning today and take your AI career to the next leve

[datascienceunicorn]

HT The Batch @deeplearning.ai

[trendsnova]

5 Essential AI Courses to Take in 2025 — No Matter Your Industry

Your fastest path to mastering AI skills that top companies are hiring for

AI Isn't Optional Anymore — It's the New Literacy

If there's one capability that will determine achievement in 2025 and beyond, it's artificial intelligence. No longer the exclusive province of Silicon Valley engineers, AI is now part of the everyday arsenal in marketing, education, finance, design, and healthcare.

A recent report from McKinsey estimates AI has the potential to inject more than $13 trillion into the economy by 2030. That's not a niche—it's a revolution. And those who know how to tap it will have a huge career advantage.

The best part? You don't require a computer science degree to get started. Nowadays, top AI education is a click away. The next five courses are some of the most prestigious and useful available, supported by giants like Google, Stanford, and DeepLearning.AI.

Google AI Essentials (Coursera) Best For: Complete beginners looking for a reliable, hands-on primer Google AI Essentials aims to equip you with a solid understanding of how AI works and how to apply it in your role, even if tech is not your background. It touches on practical uses of AI and even includes exercises to create your first AI-powered tools with Google's suite.

With a Google and Coursera certificate, this course is unique on a résumé and enables professionals to begin applying AI quickly in content writing, admin tasks, or data analysis.

AI For Everyone by Andrew Ng (Coursera) Best For: Entrepreneurs, managers, and non-technical teams Teased out by Coursera co-founder and former Google Brain boss Andrew Ng, a legendary in the field, the course is not about code but strategy for AI—how to think about the role of AI in business and society.

It’s perfect for decision-makers who want to speak the language of AI without writing a single line of code. You’ll learn how to identify which problems AI can solve, and how to build teams around those solutions.

Machine Learning Specialization (Stanford + DeepLearning.AI) Best For: Learners who want depth, and a Stanford-backed certificate If you're willing to dive deeper, this three-course specialisation—again taught by Andrew Ng—teaches the principles of supervised learning, unsupervised learning, and ML engineering best practices.

This is one of the best-known ML programmes in the world and provides you with a solid grounding to transition into AI work or create your own projects. It's an essential if you're keen on the technical aspects.

Prompt Engineering for ChatGPT (DeepLearning.AI + OpenAI) Best For: Creators, marketers, copywriters, and researchers Prompt engineering is rapidly turning into the most sought-after AI skill. In this course, you learn how to effectively interact with large language models such as ChatGPT so you can obtain the most accurate and creative output.

You will discover how to frame prompts for various purposes—summarizing, content writing, programming assistance, and more. Whether you are writing articles, emails, code, or strategies, prompt mastery is a productivity shortcut to 10x.

AI Product Management (Duke University on Coursera) Ideal For: Future product managers and startup entrepreneurs AI isn't merely about creating tools—it's about creating the right tools. This Duke University course is designed to get you to market with AI-powered products.

You'll learn to design, test, and release AI systems with consideration for user requirements, data ethics, and risk. With case studies and frameworks from leading product leaders, it's ideal for professionals who want to drive AI innovation in their firm or startup.

Why These Courses Matter These aren't random YouTube tutorials. Each one is instructed by Stanford, Google, OpenAI, or top university experts. More significantly, they provide you with practical know-how that's applicable in almost every profession.

If you are a writer wanting to apply AI for quicker content generation or a manager seeking to revolutionize your company's process, these courses will make you AI-literate—quickly.

Final Thought AI is not just a passing trend—it’s the skill that will define career trajectories for the next decade. The sooner you get started, the further ahead you’ll be when everyone else starts catching up.

Choose one course today, block 30 minutes on your calendar, and start your journey. You’ll thank yourself in six months.

[nikhilvaidyahrc]

Top 5 AI Certifications That Are Actually Worth It in 2025

Published by Prism HRC – Leading IT Recruitment Agency in Mumbai

Let’s face it, in 2025, AI is not "nice to know." It’s everywhere. From chatbots and content marketing to finance and medicine, artificial intelligence is the force working behind the scenes. That also means employers are actively searching for professionals who understand AI or at least know how to work alongside it.

But with countless online courses out there, it’s tough to know which certifications actually carry weight. Which ones make your resume stand out to real hiring managers and recruiters?

We’ve curated the top five AI certifications that are genuinely worth your time, effort, and investment in 2025, whether you’re a fresher, a seasoned techie, or someone switching careers.

Google Professional Machine Learning Engineer

Why it’s worth it: This certification shows that you can design, develop, and deploy machine learning models on Google Cloud. It’s widely respected in the industry, especially if you’re eyeing cloud-based AI roles.

Who it’s for: Mid-level professionals, data scientists, ML engineers

What you'll learn:

Defining machine learning problems

Feature engineering

Model architecture and deployment

Tools like Vertex AI, BigQuery, and TensorFlow

Bonus tip: Just having Google’s name on your resume adds major credibility, especially if you're applying to MNCs or product companies.

IBM Applied AI Professional Certificate (via Coursera)

Why it’s worth it: This course is one of the most beginner-friendly yet hands-on AI certifications out there. It teaches you practical tools and includes real-world projects you can add to your portfolio.

Who it’s for: Freshers, career changers, and even non-programmers curious about AI

What you'll learn:

Foundations of AI

Python programming for AI

IBM Watson tools and services

How to build chatbots and deploy AI applications

Pro tip: The included labs and projects are great for showcasing your work on LinkedIn or GitHub.

Microsoft Certified: Azure AI Fundamentals

Why it’s worth it: A solid starting point for anyone looking to understand AI through the lens of Microsoft’s Azure platform. This course makes complex AI ideas approachable without diving into deep code.

Who it’s for: Newcomers, business analysts, marketers, and non-tech professionals exploring a switch to AI

What you'll learn:

Core machine learning and AI principles

Natural language processing, computer vision

Responsible AI practices

Use cases and tools in Azure

Why it stands out: If you’re applying to companies already using Microsoft tools, this certification puts you ahead of the pack.

Stanford Online: Machine Learning Specialization by Andrew Ng (on Coursera)

Why it’s worth it: Andrew Ng is a well-known name in the AI world, and his course has helped millions break into machine learning. The 2025 version is updated, relevant, and perfect for serious learners who want a deep understanding.

Who it’s for: Developers, tech enthusiasts, aspiring machine learning engineers

What you’ll learn:

Supervised learning and neural networks

Bias-variance tradeoff

Decision trees

Model evaluation and tuning

What makes it special: This isn’t just a theory-heavy course. It helps you understand how machine learning actually works, and that knowledge is rare and respected.

DeepLearning.AI’s Generative AI with LLMs Specialization

Why it’s worth it: Let’s be honest, generative AI is everywhere right now. Whether you’re playing with ChatGPT or building AI tools at work, this course puts you in sync with the future.

Who it’s for: Developers, content creators, product managers, and tech professionals working with AI APIs

What you’ll learn:

Prompt engineering strategies

How large language models function

Fine-tuning LLMs

Building ethically sound GenAI applications

Hot tip: If you're interviewing for product, content, or R&D roles related to AI, this certification will make you stand out.

Before you go

Let’s cut through the noise. There are tons of AI courses out there, but only a few actually help you grow. These five certifications offer real skills, portfolio projects, and recruiter-approved credibility.

If you’re planning to enter AI, grow in your current role, or shift from another domain, one of these certifications could be the best decision you make in 2025.

Still unsure which AI path is right for your career?

Prism HRC can help you make the smart move. We match skilled talent with companies hiring in AI, data, and cloud, and we know exactly what certifications employers are asking for right now.

Based in Gorai-2, Borivali West, Mumbai Website: www.prismhrc.com Instagram: @jobssimplified LinkedIn: Prism HRC

[eagletflysolutions]

Best Data Science Certifications & Courses

If you are one of those people who prefer more in-depth learning material, this online data science course might be the perfect fit for you. Similar to the previously discussed option, this course is designed to help you build an even stronger data science knowledge foundation. The first on our list is a data science course created to give you a strong foundation of knowledge in the field. The course was created with beginners in mind and covers the most important information new data scientists might need. The program includes over hours of instruction and numerous practice-based assessments that simulate real-world data analytics scenarios - data science courses in Patel Nagar.

Essentially, it comes down to doing what you’re learning when you take a course and learn a skill, apply it to a real project immediately. Working through real-world projects, you are genuinely interested in helps solidify your understanding and proves you know what you’re doing. Python is used in this course, and many lectures go through the intricacies of the various data science libraries to work through real-world, exciting problems - python programming in Patel Nagar.

It will give the students an opportunity to demonstrate their data science skills to potential employers. Courses include introduction to data science, exploratory data analysis and visualization, big data management and machine learning. Upon completion of the program, students will have hands-on experience analyzing data using exploratory data analysis and advanced visualization, presenting statistical analysis and building forecasting models. . Students use data science tools to collect and analyze data and create models to address research questions about the information they’re investigating.

They learn data analysis applications using a four-part process, including gathering data, finding patterns, looking for insights in the patterns using the programming language and making informed decisions. The report is helpful for institutes offering these programmes to understand where they stand compared to other courses and identify areas of improvement. Skills required for this include proficiency in programming languages such as Python and R, as well as a deeper understanding of statistical methods and machine learning. As the title suggests, this course from DeepLearning.ai has a particular focus on mathematics for data scientists. For more information, please visit our site https://eagletflysolutions.com/ 

[tristinaautumn]

SEM 1 - 14/4/25 - 14/10/25

Semester 1 Members

Tristina Autumn - Engineer

Hermione Granger - Engineer

Nanami Kento - Finance

Gojo Satoru - Business

Erwin Smith - Politics

Levi Ackerman - Politics

Getou suguru - Law

Paris Geller - Doctor

Yu Haibara - Doctor

Semester 1 goal -

Career goal -

Publish 2 technical papers

Apply for 1 patent

Course to complete - CS50 | Python | C | C++ | DeepLearning.ai courses

Finish Image processing related material - Textbook | Image processing Lecture, Notebook, Lab work

Deep learning lectures | Machine and deep learning notes | My multimedia systems notes | Lab work | MMS assignment | 1sem paper assignment

Establish myself as a credible and reliable employee

COA | OS | MPU | MCU | Dive into the world of embedded systems

Physical Health Goal - WALK | DANCE | STRETCH | BREATHE | MEDITATE

Go from 75kg to 65kg

Mental Health Goal - Therapy session every week Saturday 8 pm to 9 pm

Hobbies Make one cute aesthetic web project

Learn Uke

Learn Skateboard

Learn knife painting

Learn Japanese

Learn German

Read 7 books (manga not counted!!!)

Semester 1 Reward - Japan in December 2025

[asadmukhtarr]

Machine Learning Yearning" is a practical guide by Andrew Ng, a pioneer in the field of artificial intelligence and machine learning. This book is part of the deeplearning.ai project and is designed to help you navigate the complexities of building and deploying machine learning systems. It focuses on strategic decision-making and best practices rather than algorithms or code. Below is a step-by-step breakdown of the outcomes you can expect after reading this book, presented in a user-friendly manner:

[aishwaryaanair]

Crack the AI Code: Essential Certifications for Tech Enthusiasts

Artificial Intelligence (AI) is revolutionizing industries, from healthcare to finance, cybersecurity to automation. Whether you’re a software developer, engineer, or simply an AI enthusiast, gaining a strong foundation in AI can open doors to exciting career opportunities.

AI certifications help bridge the knowledge gap by providing structured learning, hands-on experience, and industry-recognized credentials. But with so many certifications available, how do you choose the right one?

Why AI Certifications Matter for Tech Enthusiasts

The demand for AI professionals has skyrocketed, with companies looking for individuals skilled in machine learning, deep learning, natural language processing (NLP), and AI-driven automation. Whether you are a beginner or an experienced developer, an AI certification can:

Enhance your technical skills in AI, machine learning, and data science.

Boost your career prospects by demonstrating expertise in cutting-edge AI tools.

Provide hands-on experience with real-world AI applications.

Help you stay ahead in an evolving job market where AI is reshaping industries.

Now, let’s dive into the top AI certifications for tech enthusiasts.

Top AI Certifications to Crack the AI Code

1. AI+ Everyone™ by AI Certs

For those who are passionate about AI but don’t know where to start, AI+ Everyone™ by AI Certs is an excellent choice. This certification is designed to introduce AI fundamentals in an accessible way, making it ideal for beginners and tech professionals who want to understand AI’s real-world applications.

Key Topics Covered:

✔ AI Fundamentals: Understanding how AI works and its role in various industries.   ✔ Machine Learning Basics: Introduction to key ML concepts and algorithms.   ✔ AI in Business & Society: Exploring AI’s impact on industries such as healthcare, finance, and marketing.   ✔ Ethical AI: Understanding bias, fairness, and responsible AI development.

This certification provides a comprehensive foundation in AI and is perfect for tech enthusiasts looking to get started in the field.

2. Deep Learning Specialization by DeepLearning.AI (Coursera)

Taught by Andrew Ng, this specialization is one of the most recognized AI certifications in the industry. It focuses on deep learning, neural networks, and AI model development.

Key Topics Covered:

✔ Neural Networks and Deep Learning   ✔ Structuring AI Projects and Optimization Techniques   ✔ Convolutional Neural Networks (CNNs) for Image Processing   ✔ Sequence Models and Natural Language Processing (NLP)

This course is ideal for developers, data scientists, and engineers looking to master deep learning concepts.

3. IBM AI Engineering Professional Certificate (Coursera)

IBM offers this professional certification for individuals who want to gain hands-on experience with AI technologies and machine learning models.

Key Topics Covered:

✔ Machine Learning with Python   ✔ Deep Learning and Neural Networks   ✔ AI Applications in Real-World Scenarios   ✔ Building AI Models Using IBM Watson

This certification is best for tech enthusiasts who want a career in AI development, data science, or machine learning engineering.

4. Microsoft Certified: Azure AI Engineer Associate

This certification is designed for professionals looking to deploy AI solutions using Microsoft Azure’s AI services, including computer vision, NLP, and chatbot development.

Key Topics Covered:

✔ AI and Machine Learning Model Development   ✔ Azure Cognitive Services and AI-Powered Applications   ✔ Data Science Pipelines and Model Training   ✔ Responsible AI and Ethics in AI Development

If you’re interested in cloud-based AI solutions and want to work with Microsoft Azure AI, this certification is an excellent choice.

How AI Certifications Benefit Tech Enthusiasts

1. Gain Hands-On AI Experience

AI certifications often include practical projects and case studies, helping you apply AI concepts to real-world scenarios.

2. Build a Strong AI Skillset

A structured AI certification program teaches essential AI tools, programming languages (Python, TensorFlow, PyTorch), and data science techniques.

3. Increase Career Opportunities

AI-certified professionals can explore high-paying job roles, including:

AI Engineer

Data Scientist

Machine Learning Engineer

AI Researcher

Robotics Specialist

4. Stay Updated with AI Trends

The AI industry evolves rapidly, and certifications help tech enthusiasts stay ahead of the curve by learning the latest AI advancements.

How to Choose the Right AI Certification

With many AI certifications available, consider the following when selecting the best one for you:

✔ Your Skill Level: If you’re a beginner, opt for AI+ Everyone™ by AI Certs or AI for Everyone by DeepLearning.AI. For experienced tech professionals, IBM AI Engineering or Deep Learning Specialization are better choices.

✔ Hands-On Learning: Choose a certification that includes real-world projects and practical AI applications.

✔ Industry Recognition: Certifications from IBM, Microsoft, and DeepLearning.AI carry weight in the job market.

✔ Career Goals: If you’re interested in AI development, go for Deep Learning Specialization. If you prefer cloud-based AI, choose Microsoft’s Azure AI Certification.

Conclusion

The AI revolution is here, and tech enthusiasts who master AI concepts will have a competitive edge in the job market. Whether you’re a developer, engineer, or AI enthusiast, earning an AI certification is an excellent way to crack the AI code and future-proof your career.

The AI+ Everyone™ by AI Certs is a great starting point for beginners, while courses like Deep Learning Specialization, IBM AI Engineering, and Microsoft Azure AI Certification provide advanced AI skills for experienced professionals.

By investing in AI certifications, you’re not just gaining knowledge — you’re unlocking opportunities in a world that’s becoming increasingly driven by artificial intelligence.

[marketingaiblogs]

AI vs. Machine Learning Certifications: Which One Should You Choose?

Understanding AI and ML

Before diving into certifications, it’s essential to understand the difference between AI and ML. AI is a broad field that encompasses various technologies designed to simulate human intelligence, including natural language processing, robotics, and computer vision. ML, a subset of AI, focuses on algorithms that allow computers to learn from and make predictions based on data.

Why Get Certified?

Certifications can provide several benefits:

Credibility: Certifications from reputable institutions can enhance your resume and make you stand out to employers.

Skill Validation: They validate your skills and knowledge, proving your expertise in a specific area.

Career Advancement: Certifications can open up new job opportunities and lead to higher salaries.

Top AI Certifications for 2025

Professional Certificate in Computer Science for AI by Harvard University

Duration: 5 months

Format: Self-paced

Overview: This course covers critical real-world problems and prepares you for a future-proof AI career

2. Artificial Intelligence Graduate Certificate by Stanford School of Engineering

Duration: Varies

Format: Online

Overview: Taught by renowned faculty, this program dives deep into AI principles, natural language processing, and computer vision

3. Certified AI Transformation Leader (CAITL™) by USAII®

Duration: Flexible

Format: Self-paced with live masterclasses

Overview: Ideal for business leaders and AI enthusiasts, this certification includes masterclasses by industry leaders

Explore AICERT’s wide range of AI certifications, and don’t forget to use the code NEWUSERS25 for a 25% discount on all courses. Click here to start your journey into AI today!

“Have questions or are ready to take the next step in your AI certification journey? Reach out to us at AI CERTs — our team is here to guide you every step of the way!”

Top ML Certifications for 2025

1. Machine Learning Specialization by Stanford University and DeepLearning.AI

Duration: 2 months

Format: Online, self-paced

Overview: This specialization covers the fundamentals of ML, including supervised and unsupervised learning

2. Google Professional Machine Learning Engineer

Duration: Varies

Format: Online

Overview: This certification validates your ability to design, build, and productionize ML models using Google Cloud technologies

3. IBM AI Engineering Professional Certificate

Duration: 6 months

Format: Online

Overview: This program covers machine learning, deep learning, and AI engineering, making it suitable for those looking to advance their technical skills

Choosing the Right Certification

When deciding between AI and ML certifications, consider the following factors:

Career Goals: Determine whether you want to focus on the broader field of AI or specialize in ML. AI certifications are ideal for those looking to work on diverse AI applications, while ML certifications are perfect for those interested in data-driven decision-making and predictive modeling.

Current Skill Level: Assess your current knowledge and experience. If you’re new to the field, starting with a foundational certification in AI or ML might be beneficial.

Industry Demand: Research the demand for AI and ML skills in your industry. Some sectors may prioritize AI expertise, while others may require specialized ML knowledge.

Learning Format: Choose a certification that fits your learning style and schedule. Online, self-paced courses offer flexibility, while live classes provide interactive learning experiences.

Conclusion

Both AI and ML certifications can significantly boost your career in 2025. The key is to align your choice with your career goals, current skill level, and industry demands. Whether you choose to pursue an AI certification or an ML certification, investing in your education will undoubtedly pay off in the long run.

[levysoft]

[...]

o3-mini, per esempio, nella sua manifestazione all’interno di ChatGPT non permette di allegare documenti (il precedente o1 non accetta testi e PDF), mentre in Perplexity sì.

Possiamo immaginare che OpenAI non abbia incluso questa funzionalità anche perché i modelli di reasoning mangiano parte della finestra di contesto con la catena di pensieri che usano per poter esprimere la loro potenza e che, anche se non viene riportata nel prompt successivo, contribuisce a rendere meno ampia la finestra a ogni prompt. Questo concetto viene espresso bene da un corso di DeepLearning.ai su o1 curato anche da OpenAI.

Ma ci potrebbero essere anche spiegazioni architetturali come una tokenizzazione degli allegati costosa in termini computazionali che può introdurre errori o ambiguità che complicano ulteriormente il reasoning del modello.

(via Uso dell’IA per trovare clausole nascoste nei contratti (Parte II): i modelli “tradizionali” sono vincenti | DDay.it)

[educationtech]

Best AI Courses Online for Free in 2025 - Arya College

Arya College of Engineering & I.T. has some of the best online resources to learn Artificial Intelligence (AI) for free, suitable for beginners:

1. The Elements of AI

Overview: A comprehensive online course created by the University of Helsinki, designed to demystify AI for everyone, regardless of their background.

Content: The course includes two main parts:

Introduction to AI: Covers basic concepts without complicated math or programming.

Building AI: Focuses on algorithms and requires some basic Python skills.

Website: Elements of AI 

 

2. IBM SkillsBuild

Overview: Offers a variety of free courses focused on foundational AI knowledge.

Key Courses:

AI Foundations: Covers the basics of AI, including natural language processing and ethical considerations.

Build Your Own Chatbots: A hands-on project to enhance practical skills.

Website: IBM Skills Build 

 

3. Class Central

Overview: A platform that aggregates free online courses from various universities and institutions.

Features: Offers over 15,500 AI-related courses, allowing users to filter by institution and subject matter.

Website: Class Central 

 

4. Infobip's Curated List

Overview: A collection of free AI courses from reputable providers such as Microsoft and Harvard University.

Highlighted Courses:

Generative AI for Everyone by DeepLearning.AI: An overview suitable for all audiences.

Introduction to Responsible AI by Google: Discusses ethical implications in AI development.

Website: Infobip

 

5. Coursera

Overview: Offers a range of free courses from top universities and organizations, although some may charge for certificates.

Popular Courses:

Introduction to Artificial Intelligence (AI) by IBM.

Generative AI for Software Development by DeepLearning.AI.

Website: Coursera

6. edX

Overview: Provides access to free courses from prestigious institutions covering various aspects of AI.

Content Areas: Includes programming for intelligent agents, ethics in AI, and advanced topics like robotics and machine learning.

Website: edX

These resources offer a solid foundation in artificial intelligence, catering to different learning styles and preferences. Whether you’re looking for theoretical knowledge or hands-on projects, these platforms provide valuable opportunities to start your journey in AI.

[caalaadd]

Generative AI for Everyone Free Course 2025

Are you looking for AI courses? Generative AI for Everyone Free Course is an excellent opportunity to learn Artificial Intelligence. This free AI course is offered by DeepLearning.AI through Coursera and is the perfect opportunity to learn generative AI for beginners. It is an introductory-level course and does not require previous knowledge of artificial intelligence or coding skills. It is one…

[shafaqsa]

"سدايا" تفتح التسجيل في "مسارات الذكاء الاصطناعي"

  أعلنت الهيئة السعودية للبيانات والذكاء الاصطناعي “سدايا”، ممثلة في أكاديميتها اليوم عن فتح باب التسجيل في برنامج المسارات المتقدمة في الذكاء الاصطناعي لبناء قدرات 500 متخصص ومتخصصة من المؤهلين والمهتمين بالمجالات التقنية، وذلك عبر 4 مسارات مقدمة من DeepLearning.AI وجامعة ستانفورد، وتشمل: تعلم الآلة، ومعالجة اللغات ال��بيعية، والذكاء الاصطناعي التوليدي، والرؤية الحاسوبية. ويعد برنامج المسارات…

[govindhtech]

Intel Tiber AI Cloud: Intel Tiber Cloud Services Portfolio

Introducing Intel Tiber AI Cloud

Today Intel excited to announce the rebranding of Intel Tiber AI Cloud, the company’s rapidly expanding cloud offering. It is aimed to providing large-scale access to Intel software and computation for AI installations, support for the developer community, and benchmark testing. It is a component of the Intel Tiber Cloud Services portfolio.

What is Intel Tiber AI Cloud?

Intel’s new cloud service, the Intel Tiber AI Cloud, is designed to accommodate massive AI workloads using its Gaudi 3 CPUs. Rather than going up against AWS or other cloud giants directly, this platform is meant to serve business clients with an emphasis on AI computing. Tiber AI Cloud is particularly designed for complicated AI activities and offers scalability and customization for enterprises by using Intel’s cutting-edge AI processors.

Based on the foundation of Intel Tiber Developer Cloud, Intel Tiber AI Cloud represents the rising focus on large-scale AI implementations with more paying clients and AI partners, all the while expanding the developer community and open-source collaborations.

New Developments Of Intel Tiber AI Cloud

It have added a number of new features to Intel Tiber AI Cloud in the last several months:

New computing options

Nous began building up Intel’s most recent AI accelerator platform, Intel Tiber AI Cloud, in conjunction with last month’s launch of Intel Gaudi 3. We anticipate broad availability later this year. Furthermore, pre-release Dev Kits for the AI PC using the new Intel Core Ultra processors and compute instances with the new 128-core Intel Xeon 6 CPU are now accessible for tech assessment via the Preview catalog in the Intel Tiber AI Cloud.

Open source model and framework integrations

With the most recent PyTorch 2.4 release, Intel revealed support for Intel GPUs. Developers may now test the most recent Pytorch versions supported by Intel on laptops via the Learning catalog.

The most recent version of Meta’s Llama mode collection, Llama 3.2, has been deployed in Intel Tiber AI Cloud and has undergone successful testing with Intel Xeon processors, Intel Gaudi AI accelerator, and AI PCs equipped with Intel Core Ultra CPUs.

Increased learning resources

New notebooks introduced to the Learning library allow you to use Gaudi AI accelerators. AI engineers and data scientists may use these notebooks to run interactive shell commands on Gaudi accelerators. Furthermore, the Intel cloud team collaborated with Prediction Guard and DeepLearning.ai to provide a brand-new, well-liked LLM course powered by Gaudi 2 computing.

Partnerships

It revealed Intel’s collaboration with Seekr, a rapidly expanding AI startup, at the Intel Vision 2024 conference. To assist businesses overcome the difficulties of bias and inaccuracy in their AI applications, Seekr is now training foundation models and LLMs on one of the latest super-compute Gaudi clusters in Intel’s AI Cloud, which has over 1,024 accelerators. Its dependable artificial intelligence platform, SeekrFlow, is now accessible via Intel Tiber AI Cloud‘s Software Catalog.

How it Works

Let’s take a closer look at the components that make up Intel’s AI cloud offering: systems, software, silicon, and services.

Silicon

For the newest Intel CPUs, GPUs, and AI accelerators, Intel Tiber AI Cloud is first in line and Customer Zero, offering direct support lines into Intel engineers. Because of this, Intel’s AI cloud is able to provide early access to inexpensive, perhaps non-generally accessible access to the newest Intel hardware and software.

Systems

The size and performance needs of AI workloads are growing, which causes the demands on computational infrastructure to change quickly.

To implement AI workloads, Intel Tiber AI Cloud provides a range of computing solutions, including as virtual machines, dedicated systems, and containers. Furthermore, it have recently implemented high-speed Ethernet networking, compact and super-compute size Intel Gaudi clusters for training foundation models.

Program

Intel actively participates in open source initiatives like Pytorch and UXL Foundation and supports the expanding open software ecosystem for artificial intelligence. Users may access the newest AI models and frameworks in Intel Tiber AI Cloud with to dedicated Intel cloud computing that is assigned to help open source projects.

Services

The way in which developers and enterprise customers use computing AI services varies according on use cases, technical proficiency, and implementation specifications. To satisfy these various access needs, Intel Tiber AI Cloud provides server CLI access, curated interactive access via notebooks, and serverless API access.

Why It Is Important

One of the main components of Intel’s plan to level the playing field and eliminate obstacles to AI adoption for developers, enterprises, and startups is the Intel Tiber AI Cloud:

Cost performance: For the best AI implementations, it provides early access to the newest Intel computing at a competitive cost performance.

Scale: From virtual machines (VMs) and single nodes to massive super-computing Gaudi clusters, it provides a scale-out computing platform for expanding AI deployments.

Open source: It ensures mobility and prevents vendor lock-in by providing access to open source models, frameworks, and accelerator software supported by Intel.

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